The present invention relates to dynamic modeling of the pulmonary trunk using medical images, and more particularly, to pulmonary trunk modeling and percutaneous pulmonary valve implantation (PPVI) intervention planning using 4D computed tomography (CT) image data.
Valvular heart disease (VHD) is a cardiac disorder that affects a large number of patients and often requires elaborate diagnostic procedures, intervention, and long-term management. In most cases, pulmonary abnormalities occur in conjunction with other heart diseases, and can be caused by congenital defects, pulmonary hypertension, endocarditis, rheumatic fever, and carcinoid heart disease. Such conditions require constant monitoring and a complex clinical workflow, including patient evaluation, percutaneous intervention planning, valve replacement and repair, and follow-up evaluations.
Traditionally, pulmonary valve replacement has been performed surgically on an open heart, with associated risks including, high mortality, incidence of neurological damage, stroke, and repeated valve replacement. However, minimally invasive procedures for the pulmonary valve are less traumatic and reduce the risks associated with valve replacement. Percutaneous pulmonary valve implantation (PPVI) is a recently developed technique for transcatheter placement of a valve stent. Some difficulties with PPVI include the 3D/4D assessment of the pulmonary trunk morphology and in particular the right ventricle outflow track (RVOT) which must be less than 22 mm before treatment, the classification of patients suitable for the procedure, and the identification of the exact location for anchoring the stent. Hence, precise assessment of the morphology and dynamics of the pulmonary valve is crucial for the pre-procedural planning and successful intervention of PPVI.
Cardiac computed tomography (CT) imaging is often performed when high spatial resolution, soft tissue contrast, or dynamics is essential. The key advantage of cardiac CT imaging is the ability to acquire multiple non-invasive and accurate scans required for evaluation. In standard clinical settings, cardiac CT imaging is used to gain information about the shape of the RVOT and the pulmonary artery. In such cases, the acquired 4D CT data is usually translated into sets of 2D planes for manual quantification and visual evaluation, due to lack of appropriate methods and tools for processing the 3D/4D image data. Measurements may be tedious to obtain and are often affected by inaccuracies, as 2D alignment and sectioning is ambiguous and can lead to misinterpretation of the image data.